Controlling parameters proportional integral derivative of DC motor using a gradient-based optimizer

Widi Aribowo, R. Rahmadian, M. Widyartono, A. Wardani, Aditya Prapanca, L. Abualigah
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Abstract

In this paper, a gradient-based optimizer (GBO) algorithm is presented to optimize the parameters of a proportional integral derivative (PID) controller in DC motor control. The GBO algorithm which mathematically models and mimics is inspired by the gradient-based Newton method. It was developed to address various optimization issues. To determine the performance of the proposed method, a comparison method with the ant colony optimization (ACO) method. It was compared using the integral of time multiplied absolute error (ITAE). They are most popularly used in the literature. From the test results, the proposed method is promising and has better effectiveness. The proposed method, namely GBO-PID, shows the best performance.
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利用基于梯度的优化器控制直流电机的参数比例积分导数
本文提出了一种基于梯度的优化算法(GBO),用于优化直流电机控制中比例积分导数(PID)控制器的参数。GBO 算法在数学模型上模仿了基于梯度的牛顿方法。它是为解决各种优化问题而开发的。为了确定所提方法的性能,采用了与蚁群优化(ACO)方法进行比较的方法。该方法使用时间乘以绝对误差积分法(ITAE)进行比较。它们是文献中最常用的方法。从测试结果来看,所提出的方法很有前途,而且效果更好。所提出的方法,即 GBO-PID 显示出最佳性能。
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